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一種新的數(shù)據(jù)流模糊聚類方法

孫力娟 陳小東 韓崇 郭劍

孫力娟, 陳小東, 韓崇, 郭劍. 一種新的數(shù)據(jù)流模糊聚類方法[J]. 電子與信息學(xué)報, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415
引用本文: 孫力娟, 陳小東, 韓崇, 郭劍. 一種新的數(shù)據(jù)流模糊聚類方法[J]. 電子與信息學(xué)報, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415
Sun Li-juan, Chen Xiao-dong, Han Chong, Guo Jian. New Fuzzy-Clustering Algorithm for Data Stream[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415
Citation: Sun Li-juan, Chen Xiao-dong, Han Chong, Guo Jian. New Fuzzy-Clustering Algorithm for Data Stream[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1620-1625. doi: 10.11999/JEIT141415

一種新的數(shù)據(jù)流模糊聚類方法

doi: 10.11999/JEIT141415
基金項目: 

國家自然科學(xué)基金(61171053, 61300239),教育部博士點基金(20113223110002),中國博士后科學(xué)基金(2014M551635)和江蘇省博士后科研資助計劃項目(1302085B)資助課題

New Fuzzy-Clustering Algorithm for Data Stream

  • 摘要: 針對數(shù)據(jù)流上的聚類任務(wù)受到時間、空間限制等問題,該文提出一種基于權(quán)值衰減的數(shù)據(jù)流模糊微簇聚類算法(WDSMC)。該算法使用改進的帶權(quán)值的模糊C均值算法進行處理,并采用微簇結(jié)構(gòu)和權(quán)值時間衰減結(jié)構(gòu)提高聚類質(zhì)量。實驗表明,相對于現(xiàn)有的數(shù)據(jù)流加權(quán)模糊C均值聚類(SWFCM)算法和StreamKM++算法而言,WDSMC算法具有更好的聚類精度。
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出版歷程
  • 收稿日期:  2014-11-05
  • 修回日期:  2015-03-20
  • 刊出日期:  2015-07-19

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